Read to learn how teachers can incorporate data science into their classrooms, how students can learn at home and what kinds of resources are available.
Resources
Cybercriminals target health care facilities because they store valuable patient data, such as identities, bank accounts, and loans. Here’s what you can do to protect yourself.
Technology companies collect first- and third-party data using collection methods. They use this data to develop effective advertising campaigns and increase engagement or profitability. Read to learn more!
Blockchain technology addresses vulnerabilities in IoT security, such as malware and botnets. However, there’s a learning curve for implementing a decentralized and encrypted data storage system and validation mechanisms are key.
The Internet of Things (IoT) already has many uses in the classroom, and its future remains bright. However, IoT tech should always be integrated into educational scenarios with care to avoid creating security risks or leaving behind students with different learning styles and needs.
Big data governance sets company policies and procedures for data collection, access and analysis. Companies with robust data governance plans avoid compliance penalties and have more efficient access to data.
From protecting our sensitive data to defending businesses against online threats, cybersecurity is essential in protecting internet-connected systems from cyberattacks. Security breaches cost businesses millions of dollars every year, so it is necessary to keep up to date on the latest advancements. Professional organizations, blogs, websites, books and conferences are all great ways to stay …
As a new graduate, one of your biggest obstacles may be landing your first job. With no experience, it can be tough to impress employers or prove you have a strong work ethic and the ability to tackle job duties responsibly and efficiently. Once you’ve completed your degree in data science, it’s important to learn …
The life cycle of data science projects can vary, but most projects include problem identification, data mining, data analysis and deployment of predictive algorithms.
Learn about 5 key areas in the telecom industry where data scientists are finding careers and creating value (plus some fun history and info on regulations).